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How customers motive attributions impact intentions to use an interactive kiosk in-store

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  • van de Sanden, Stephanie
  • Willems, Kim
  • Brengman, Malaika

Abstract

This study explores the effect of customers motive attributions that is, the motives customers ascribe to a retailer for introducing interactive kiosks into the store, on their expectations of the technology and usage intentions. We study two types of motive attribution: (1) to self-serve the retailer's own economic goals or (2) to better serve customers' needs. Data were collected at a do-it-yourself retailer that recently installed interactive kiosks. Empirical results demonstrate that customer-serving motive attributions improve intention to use, both via expected performance and via expected enjoyment. Our findings also demonstrate that customers expect the interactive kiosk to be less enjoyable when attributing self-serving retailer motives. Managerial implications are discussed along with direction for future research.

Suggested Citation

  • van de Sanden, Stephanie & Willems, Kim & Brengman, Malaika, 2022. "How customers motive attributions impact intentions to use an interactive kiosk in-store," Journal of Retailing and Consumer Services, Elsevier, vol. 66(C).
    • Handle: RePEc:eee:joreco:v:66:y:2022:i:c:s096969892200011x
    DOI: 10.1016/j.jretconser.2022.102918
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    1. Brengman, Malaika & De Gauquier, Laurens & Willems, Kim & Vanderborght, Bram, 2021. "From stopping to shopping: An observational study comparing a humanoid service robot with a tablet service kiosk to attract and convert shoppers," Journal of Business Research, Elsevier, vol. 134(C), pages 263-274.
    2. Markus Blut & Cheng Wang, 2020. "Technology readiness: a meta-analysis of conceptualizations of the construct and its impact on technology usage," Journal of the Academy of Marketing Science, Springer, vol. 48(4), pages 649-669, July.
    3. Hair, Joe F. & Howard, Matt C. & Nitzl, Christian, 2020. "Assessing measurement model quality in PLS-SEM using confirmatory composite analysis," Journal of Business Research, Elsevier, vol. 109(C), pages 101-110.
    4. Yogesh K. Dwivedi & Nripendra P. Rana & Anand Jeyaraj & Marc Clement & Michael D. Williams, 2019. "Re-examining the Unified Theory of Acceptance and Use of Technology (UTAUT): Towards a Revised Theoretical Model," Information Systems Frontiers, Springer, vol. 21(3), pages 719-734, June.
    5. Guan, Xinhua & Xie, Lishan & Shen, Wen-Guo & Huan, Tzung-Cheng, 2021. "Are you a tech-savvy person? Exploring factors influencing customers using self-service technology," Technology in Society, Elsevier, vol. 65(C).
    6. Chang, Kuo-Chien & Hsu, Chia-Lin & Hsu, Ya-Ti & Chen, Mu-Chen, 2019. "How green marketing, perceived motives and incentives influence behavioral intentions," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 336-345.
    7. Schweitzer, Virginie & Simon, Françoise, 2021. "Self-construals as the locus of paradoxical consumer empowerment in self-service retail technology environments," Journal of Business Research, Elsevier, vol. 126(C), pages 291-306.
    8. Grewal, Dhruv & Levy, Michael & Kumar, V., 2009. "Customer Experience Management in Retailing: An Organizing Framework," Journal of Retailing, Elsevier, vol. 85(1), pages 1-14.
    9. Mizerski, Richard W & Golden, Linda L & Kernan, Jerome B, 1979. "The Attribution Process in Consumer Decision Making," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 6(2), pages 123-140, Se.
    10. Langan, Ryan & Kumar, Anand, 2019. "Time versus money: The role of perceived effort in consumers' evaluation of corporate giving," Journal of Business Research, Elsevier, vol. 99(C), pages 295-305.
    11. Lunardo, Renaud & Mbengue, Ababacar, 2013. "When atmospherics lead to inferences of manipulative intent: Its effects on trust and attitude," Journal of Business Research, Elsevier, vol. 66(7), pages 823-830.
    12. Weiner, Bernard, 2000. "Attributional Thoughts about Consumer Behavior," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 27(3), pages 382-387, December.
    13. Pillai, Rajasshrie & Sivathanu, Brijesh & Dwivedi, Yogesh K., 2020. "Shopping intention at AI-powered automated retail stores (AIPARS)," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    14. Andrea C. Morales, 2005. "Giving Firms an "E" for Effort: Consumer Responses to High-Effort Firms," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 31(4), pages 806-812, March.
    15. Demirkan, Haluk & Spohrer, Jim, 2014. "Developing a framework to improve virtual shopping in digital malls with intelligent self-service systems," Journal of Retailing and Consumer Services, Elsevier, vol. 21(5), pages 860-868.
    16. John Hulland & Hans Baumgartner & Keith Marion Smith, 2018. "Marketing survey research best practices: evidence and recommendations from a review of JAMS articles," Journal of the Academy of Marketing Science, Springer, vol. 46(1), pages 92-108, January.
    17. Pantano, Eleonora & Vannucci, Virginia, 2019. "Who is innovating? An exploratory research of digital technologies diffusion in retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 49(C), pages 297-304.
    18. Ratchford, Mark & Ratchford, Brian T., 2021. "A cross-category analysis of dispositional drivers of technology adoption," Journal of Business Research, Elsevier, vol. 127(C), pages 300-311.
    19. Viswanath Venkatesh & Fred D. Davis, 2000. "A Theoretical Extension of the Technology Acceptance Model: Four Longitudinal Field Studies," Management Science, INFORMS, vol. 46(2), pages 186-204, February.
    20. Renaud Lunardo & Dominique Roux, 2015. "In-store arousal and consumers’ inferences of manipulative intent in the store environment," Post-Print hal-02022185, HAL.
    21. Puccinelli, Nancy M. & Goodstein, Ronald C. & Grewal, Dhruv & Price, Robert & Raghubir, Priya & Stewart, David, 2009. "Customer Experience Management in Retailing: Understanding the Buying Process," Journal of Retailing, Elsevier, vol. 85(1), pages 15-30.
    22. Virginie Schweitzer & Françoise Simon, 2021. "Self-construals as the locus of paradoxical consumer empowerment in self-service retail technology environments," Post-Print hal-03110766, HAL.
    23. Gursoy, Dogan & Chi, Oscar Hengxuan & Lu, Lu & Nunkoo, Robin, 2019. "Consumers acceptance of artificially intelligent (AI) device use in service delivery," International Journal of Information Management, Elsevier, vol. 49(C), pages 157-169.
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